Catch the star! Spatial information activates the manual motor system

Previous research demonstrated a close bidirectional relationship between spatial attention and the manual motor system. However, it is unclear whether an explicit hand movement is necessary for this relationship to appear. A novel method with high temporal resolution–bimanual grip force registration–sheds light on this issue. Participants held two grip force sensors while being presented with lateralized stimuli (exogenous attentional shifts, Experiment 1), left- or right-pointing central arrows (endogenous attentional shifts, Experiment 2), or the words "left" or "right" (endogenous attentional shifts, Experiment 3). There was an early interaction between the presentation side or arrow direction and grip force: lateralized objects and central arrows led to a larger increase of the ipsilateral force and a smaller increase of the contralateral force. Surprisingly, words led to the opposite pattern: larger force increase in the contralateral hand and smaller force increase in the ipsilateral hand. The effect was stronger and appeared earlier for lateralized objects (60 ms after stimulus presentation) than for arrows (100 ms) or words (250 ms). Thus, processing visuospatial information automatically activates the manual motor system, but the timing and direction of this effect vary depending on the type of stimulus.

Thus, previous research convincingly demonstrated a bidirectional relationship between spatial 23 attention and hand movement across various paradigms. But how automatic is this link between the 24 manual motor system and spatial processing? Is hand movement, whether ongoing or potential, a 25 necessary component for this relationship to appear? In a previous study, my colleagues and I 26 presented participants with large vs. small numerical stimuli (15) while monitoring participants' 27 spontaneous hand motor activity using two grip force sensors (16-20, for review and methodological 28 details, see 21). No manual response or explicit hand movement was required. Numerical cognition 29 research shows that small numbers are associated with the left peripersonal space, and large numbers 30 are associated with the right peripersonal space (Spatial Numerical Association of Response Codes, or 31 SNARC effect, see 22). This effect has been demonstrated with button press responses, finger 32 movements (23), eye movements (24), foot responses (25), and even full-body movements (see for 33 reviews 26,27, see for meta-analysis 28). Despite this overwhelming evidence for the presence of 34 spatial-numerical associations, we found no SNARC effect in grip force (15), either because no 35 attentional shifts appeared without explicit motor responses to numeric stimuli (cf. 29) or because the 36 manual motor system is not activated automatically by spatial information. The latter hypothesis was 37 tested explicitly in the present study. 38 The goal of the present study was to investigate the direct effects of attentional shifts on the manual 39 motor system in the absence of any motor action. A novel method, bimanual grip force recording, 40 allows monitoring motor activity in hands with millisecond resolution while participants process visual 41 stimuli. Grip force sensors measure spontaneous motor activity during action observation (30) and 42 semantic processing of motor-related language (16-20). Both hands exhibit comparable activity in 43 response to motor-related linguistic stimuli (31). 44 In the present study, I recorded grip force bimanually while manipulating participants' visual attention.
After the experiments, participants completed questionnaires including demographic data (gender, age, 74 native language, and foreign languages they speak) and physiological data (seeing problems, hearing 75 problems, motor diseases, and whether they take medications that can influence motor control). 76 Additionally, participants filled in the Edinburg Handedness Inventory (EHI, 40), where original 77 instructions were replaced with a more intuitive Likert scale as suggested elsewhere (41). Resulting 78 EHI scores range from +100 (exclusively right-handed) through 0 (ambidextrous) to -100 (exclusively 79 left-handed). All participants signed an informed consent form before the study. The study was 80 approved by the Ethics Committee at the University of Potsdam 81 (www.uni-potsdam.de/de/senat/kommissionen-des-senats/ek; study number 15/2019). 82 One participant was excluded due to a self-reported motor problem (light essential tremor) clearly 83 reflected in his force data. Another participant reported left leg paralysis, but her data were not 84 qualitatively different from the rest of the sample and thus remained in the final dataset. Only German 85 native speakers participated in the word presentation study (Experiment 3). All but one participant 86 reported having normal or corrected-to-normal vision.

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Equipment and data acquisition 88 The method followed closely the one recommended by Nazir et al. (21) for single-sensor recording. 89 Both sensors were stand-alone load cells manufactured by ATI Industrial Automation, USA 90 (www.atiia.com/Products/ft/sensors.aspx). They resembled large metal coins with 40 mm diameter and 91 14 mm height, and each weighed 57 g. Each sensor was covered from both contact sides with a 3 mm 92 plastic cover of the same diameter as the sensor itself (40 mm), resulting in a total thickness of 20 mm 93 and a total weight of 65 g per sensor (see Figure 1). These sensors record force dynamics with 94 millisecond resolution along three orthogonal axes, but only Fz force along the vertical axis through   Participants' elbows rested on the table while their hands held the sensors, thus preventing sensor 108 slippage (see Fig. 1). The distance between sensors varied from 30 to 50 cm and was not strictly 109 controlled, but both were equidistant from each participant's mid-sagittal plane. The distance from 110 participants' eyes to the screen was around 60 cm.

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Before data collection, participants practiced applying a holding force in a range between 1.5 N and 3 112 N with each hand. The sensors were represented on the screen as two circles that changed their color 113 from green ("too weak") to red ("too strong") with the pre-defined force range indicated by the grey 114 color. As soon as participants managed to turn both circles into grey, they received an instruction to 115 keep the force at this level during the whole testing session. Data collection started automatically after 116 participants held the sensor with the required force for three seconds without crossing these thresholds.

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This calibration procedure was repeated after each break and at the beginning of each experiment.

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Most participants successfully learned to perform the calibration within 15-30 seconds. There were, 119 however, a few participants who required up to two minutes during the first calibration.

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There was no cover story used for the participants. Forty-one psychology and linguistics students (13 males, 28 females; mean age = 24 years) 128 participated in the experiment. Their mean EHI score was 66 (80% had EHI score > 50; 10% had EHI 129 score between +50 and -50; 10% had EHI score < -50). All but one participant reported normal or 130 corrected-to-normal vision. No participant took medications affecting motor control.

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Stimuli and design 132 Red and yellow stars were used as stimuli in catch (go) and critical (no-go) trials accordingly. The  Task and procedure 138 After the calibration procedure described above, the experiment started. Each trial consisted of a 139 fixation dot (200 ms), followed by a stimulus (until response, but no longer than 2000 ms). The stimuli 140 were stars around 4 cm in diameter (3.82 degrees of visual angle calculated by using the formula 141 57.3*w/d; wwidth of the object; ddistance to the object), which appeared with equal probability 142 (33%) in one of three positions: at the center of the screen, or 19.5 cm left or right from the center 143 (18.62 degrees of visual angle). 75% of the stars were yellow, and red stars appeared in 25% of all 144 trials. The task was to say "yes" when a red star appeared, regardless of stimulus location. Participants 145 were asked not to rotate their heads when stars appeared laterally, but eye movements were allowed. 146 Additionally, participants were instructed not to cross their legs during the experiment. Critical trials 147 for analysis were no-go trials (yellow stars). This means that overt motor or verbal responses do not 148 contaminate grip force recordings. Such responses typically generate large artifacts in these recordings 149 (e.g., see panel A at Figures 2, 4, and 6). The experiment consisted of 360 trials with a break in the 150 middle and lasted around 15 minutes. It was preceded by a short practice (12 trials).

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Data preprocessing and analysis 152 The preprocessing of grip force data closely followed the recommendations of Nazir et al. (21,153 Experiment 2). Data were filtered at 15 Hz before analysis with a fourth-order, zero-phase, low-pass participants from 0% to 19% (mean = 2%). Those trials were discarded, but no participant was 163 excluded due to this criterion. Accuracy varied from 98% to 100% (mean = 100%); error trials were 164 excluded from further analysis.

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Overall grip force patterns are presented in Figure 2 to give readers an overview of this 166 relatively unfamiliar data type. The blue line in Figure 2A represents averaged force of both hands for 167 all accepted no-go trials. As suggested before (15), these changes will be referred to as H (high force, 168 peaks), with a number representing a time point. For example, H130 means a peak with its highest 169 point at around 130 ms after stimulus onset. As one can see, independently of a particular condition, 170 grip force produces three peaks (H130, H330, and H600). The second peak (H330) is the tallest. Figure   171 2B represents averaged grip force changes in go (dotted red line) and no-go (solid blue line) trials.

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These two lines start diverging at 250 ms after stimulus onset with force in go trials reaching its     given analysis was non-significantin such cases, it is also reported.

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The main effect of Hand was significant: grip force in the left hand was more prominent than in the 208 right hand (b = -4.261, p = .001). The interaction between Hand and Position was also significant (b = 209 4.071, p = .009). Still, since this time window is a part of a larger one (260-1000 ms) suggested by the 210 3 Cluster permutation analysis is a bootstrapping method for continuous signal. In this analysis, conditions are randomly assigned to epochs, which results in a random data structure. According to newly assigned labels, a t-statistics is calculated. The mass of the clusters exceeding a significance threshold is stored. The procedure is repeated multiple times, with the resulting distribution of random cluster masses that can be found in the dataset. The actual cluster mass is then compared with bootstrapped cluster masses, and the likelihood of the observed result is calculated. I suggest using this method in case of force registration for exploratory purposes to identify potential time windows of interest. Linear mixed-effects models are used in the present study for confirmatory analyses. cluster permutation analysis for this interaction, it was not examined further. Marginal r-squared 211 (variance explained by fixed effects, see 48) was .041, and conditional r-squared (variance explained 212 by the whole model, i.e., fixed and random effects together) was .451. See Table 1

60-130 ms, Model 1.3.
The data were restructured, and the mean-centered force of the opposite hand in 226 the same time window was included as a predictor 4 . As before, continuously coded Position (-1 = left, 227 0 = center, +1 = right) was included as fixed effect, participants were included as random intercepts. 4 The force of the opposite hand was used as a predictor in order to account for the correlation of forces due to automatic coordination between hands (49). I expect lateralized stimuli to lead to increased force on the ipsilateral side. Still, at the same time, it is clear from force patterns that the force of both hands changes simultaneously, i.e., when the force of one hand increases, so does the other (see Figures 2C, 6C, and 9C). It implies that this basic physiological mechanism might mask lateralized effects of interest. That is why I suggest using the contralateral force as a covariate and estimating the effect of interest beyond the variance explained by the contralateral force.
Function drop1 was used to identify and successively eliminate non-significant terms. The effect of 229 Position on the left-hand force (after accounting for the contralateral force) was close to significance 230 with higher force when stars were presented on the left side (b = -0.681, p = .052; marginal rsquared = 231 .073, conditional r-squared = .726; see Table 3 for details; see also Figure 4). larger right force when stimuli were presented on the right side (b = 1.316, p = .005; marginal r238 squared = .371, conditional r-squared = .408; see Table 4 for details; see also Figure 4).   Table 5) and the right force increased when the stimuli were presented on the right (b = 2.949, p < 250 .001; marginal r-squared = .092, conditional r-squared = .621; see Tables 5 and 6; see also Figure 5).  The same sample of participants as in Experiment 1 participated in this experiment.

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Stimuli and design 269 Red and yellow arrows were used as stimuli in catch (go) and critical (no-go) trials accordingly. The Task and procedure 275 After the calibration procedure already described above, the experiment started. Each trial consisted of 276 a fixation dot (200 ms), followed by a stimulus (until response, but no longer than 2000 ms).

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Participants saw an arrow around 2 cm in diameter (1.91 degrees of visual angle) with equal 278 probability (33%) pointing into one of three directions (left, right, or both). In 25% of all trials, red 279 arrows appeared, the other 75% of arrows were yellow. The task was to say "yes" when a red arrow 280 appeared. Participants were asked not to cross their legs during the experiment. Critical trials were 281 always no-go trials (yellow arrows). The experiment lasted around 15 minutes and consisted of 360 282 trials with a break in the middle. A short practice (12 trials) preceded the experiment.

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Data preprocessing and analysis 284 The same preprocessing procedures were applied as in Experiment 1. One participant had the 285 proportion of trials with force exceeding pre-defined thresholds (±500 mN) larger than 20% and thus 286 was excluded. For the remaining participants, this proportion ranged from 0% to 10% (mean = 2%).

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Force patterns are shown in Figure 6. The solid blue line in Figure 6A represents averaged force of  .089). The effect of Hand and the interaction between the two variables were not significant.
Marginal 336 r-squared was .006, and conditional r-squared was .508. See Table 8 for further details.
337  .810; see Table 9) and the right force increased when the arrows pointed to the right (b = 0.867, p =

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.013; marginal r-squared = .566, conditional r-squared = .817; see Table 10; see also Figure 8). Thus, Experiment 2 demonstrated a pattern similar to Experiment 1: left-and right-pointing arrows led to a significant force decrease in the contralateral hand. Unlike in Experiment 1, where the effect was stronger in the right hand, the magnitude of the effect in Experiment 2 was comparable across hands.

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Moreover, the effect of arrow direction was less pronounced and appeared later than the effect of star position.

Experiment 3: Word presentation
In Experiment 3, participants saw centrally presented words LINKS, RECHTS or ZENTRUM ("left", "right" or "center" in German; Note, however, that words "LINKS" and "RECHTS" are adverbs in German, while the word "ZENTRUM" is a noun). Bimanual force recording allowed to investigate dynamic involvement of the motor system into the processing of spatial information presented in a purely symbolic way, i.e., through linguistic meaning.

Participants
Only a subsample of German native speakers participated in this experiment (N = 27; mean age = 24; 9 males and 18 females). On average, participants spoke 1.85 foreign languages, most frequently English, Spanish, and French. The mean EHI score of those participants was +60, with 21 participants (78%) having EHI score > +50, 2 participants (7%) having EHI scores between +50 and -50, and 4 participants (15%) with EHI score < -50. All participants reported normal or corrected-to-normal vision. No participant took medications affecting motor control.

Stimuli and design
Red and yellow words or meaningless symbol arrays (e.g., §@#$%) were used as stimuli in catch (go) and critical (no-go) trials accordingly. The background was kept black. Experimental scripts can be found in the supplementary data (see data availability statement). Grip force was recorded bimanually.
This results in a 2 (Hand: left / right) X 3 (Word: left / center / right) within-participant design.

Task and procedure
After the calibration procedure described above, the experiment started. Each trial consisted of a fixation dot (200 ms), followed by a stimulus (until response, but no longer than 2000 ms).
Participants saw words or symbol arrays, all having a length of around 2.5 cm (2.39 degrees of visual angle) in a 25 px (19 pt) Droid Sans Mono font. Words "left", "right", and "center" appeared with equal probability. The task was to say "yes" when a red word (20% of all trials) or symbol array (20% of all trials) appeared. Participants were asked not to cross their legs during the experiment. Critical trials were always no-go with words (i.e., only real words in yellow font, 40% of all trials). In the remaining 20% of all trials, yellow symbol arrays appeared, and no response was required. The experiment consisted of 450 trials with a break in the middle and lasted around 20 minutes. A short practice (18 trials) preceded the experiment.

Data preprocessing and analysis
The same preprocessing procedures were applied as in Experiment 1. The proportion of trials with force exceeding pre-defined thresholds (±500 mN) ranged from 0% to 18% (mean = 2%), and no participant was excluded due to this criterion. Those trials were discarded. Accuracy varied from 97% to 100% (mean = 99%); error trials were excluded from further analysis. Figure 9A represents averaged force of both hands for all accepted no-go trials plotted for words only.
Independently of condition, grip force demonstrates the following pattern: there are two well-defined peaks of equal height (H130 and H350) with a slight deviation of force at the beginning of the second peak (H250). After H350, the force drops dramatically until 600 ms and remains relatively stable until the end of the epoch (1000 ms), with only a tiny wave having its peak at H850. Figure 9B represents averaged forces in go (dotted red line) and no-go (solid blue line) trials. These two lines start diverging at 230 ms after stimulus onset with force in go trials reaching its highest point (around 40 mN) at around 650 ms and remaining at this level till the end of the epoch. Figure 9C represents force averaged by condition (Hand X Word).  See Table 11 for further details.  3.2 and 3.3. The same approach was used as for Experiment 1 (see time windows 60-130 ms and 260-1000 ms). Word was re-coded as a continuous variable (left: -1; center: 0; right: 1).

250-300 ms, Models
Each force was tested separately, with the contralateral force and Word as predictors. The effect of Word was significant in the left hand: the grip force increased for the word "right" compared to the word "left" (b = 1.736, p = .047; marginal r-squared = .171, conditional r-squared = .764; see Table   12), and in the right hand the force increased for the word "left" compared to the word "right" (b = 1.690, p = .041; marginal r-squared = .166, conditional r-squared = .768; see Table 13; see also Figure   11).  conditional r-squared = .501; see Table 14), neither was it significant in the right hand (b = 0.638, p =

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.619; marginal r-squared = .188, conditional r-squared = .596; see Table 15).  Thus, the effect of Word emerged at 250-300 ms, which is later than the effect of Position (Experiment 466 1) or Direction (Experiment 2). Moreover, the grip force increased in hand contralateral to the expected one: in the right hand for the word "left" and in the left hand for the word "right". This 468 surprising finding will be discussed in detail in the last section.    In the next section, all results will be discussed in more detail.

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The present study aimed to investigate the effects of spatial processing on the manual motor system by 516 using a new method -bimanual grip force recording. In Experiment 1, participants' visual attention 517 was shifted using lateralized stimuli presentation (Experiment 1). In Experiment 2, participants were 518 centrally presented with pictographic symbols with spatial meaning (left-or right-oriented arrows). In 519 Experiment 3, participants were centrally presented with words having spatial meaning ("left" vs.

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"right"). Since a go/no-go paradigm with a verbal response in go trials was used, any observed effects 521 can only be attributed to spatial/semantic processing alone and not to motor preparation of responses.

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General pattern of grip force changes. The first important finding is that all three types of stimuli 523 (stars, arrows, and words) led to very similar initial force patterns (see Figure 12), namely two peaks 524 (around 130 and 300-350 ms after stimulus onset) followed by differentially declining force profiles. I 525 will now interpret these results in turn. in the present study but not for stars (in this study) or faces (in a previous study, unpublished). Since 545 numbers, words, and arrows are all symbolic stimuli, I hypothesize that this smaller peak around 250 546 ms reflects some process specific to the understanding of symbols.

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Suppose my hypothesis is correct and grip force reflects not only motor-related but also more general 548 cognitive processes, such as stimulus identification and preparation or inhibition of verbal responses.

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In that case, this has implications for other studies using the force registration method. In previous 550 studies of this kind (e.g., 19,21), force changes were always interpreted as specific signatures of 551 activity in the manual motor system. However, a recent study shows that even observing foot actions 552 leads to changes in grip force (30), perhaps due to automatic propagation of activity in the motor brain system see the HANDLE model, 54); the same happened with the word "right" and the right hand. To 604 further examine this hypothesis, it would be necessary to design a study following the procedure of 605 Experiment 3 but with a non-linguistic response. I predict that words will exhibit force patterns similar 606 to those in Experiments 1 and 2 in such a study since no inhibition of motor semantics should happen.

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If this is the case, this finding has implications for the research on inhibitory control: multiple 608 measures of this presumably higher-order construct often do not correlate with each other (e.g., 55).

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The reason might be that inhibitory control does not constitute a single construct but is instead highly  Although the present study shares many similarities with classical research using the Posner paradigm, 629 substantial differences in the setup and procedure should be considered when comparing the current 630 results with previous studies. First, no laterally appearing stars, arrows, or words were cues in the 631 original sense of this term: there were no "target" stimuli following them. Instead, they were 632 themselves the targets. While lateralized stars indeed led to automatic attentional shifts due to their 633 location, symbolic cues (arrows and words) could indirectly shift attention, following automatic 634 processing of their meaning, which was not necessary for the color discrimination task. The task itself 635 required merely superficial processing (60) and was not related to spatial information. These factors 636 taken together make the similarity between effects of lateralized stimuli and centrally presented arrows The present study investigated the relationship between spatial attention and the manual motor system